Knowledge evolutionary process of Artificial intelligence in E-commerce: Main path analysis and science mapping analysis

Artificial intelligence (AI) is the latest designing and interacting technology used to support organizations in the competitive electronic commerce (E-commerce) context. The studies on AI in E-commerce remain fragmentary since few papers review the evolutionary process of knowledge infrastructure. To bridge this gap, we constructed a conceptual framework from the resource orchestration perspective, and retrieved 2252 documents from the Web of Science (WoS) database dating from 1998 to 2022 to synthesize the extant research on AI in E-commerce. Specifically, we integrated main path analysis with science mapping analysis covering the strategic diagram and evolution map. Through qualitative analysis of critical nodes in main paths, this article found that knowledge disseminated around recommender systems (RSs). This article also examined the performance traits and inter-relationships of significant themes over three consecutive time zones, as well as identified four main AI-enabled outcomes (thematic areas): Optimization and decision support, Trust and personalized recommendation, Sentiment analysis, and AI theories with allied technologies. Potential research prospects and implications are proposed based on these findings. Overall, this article provides state-of-the-art information on how AI can facilitate the implementation of E-commerce operations and could serve as a stepping stone to newcomers in the scientific community.